Multimedia capturing devices are commonly used for monitoring different areas or activities such as traffic control, security control, and human health diagnosis. For example, multimedia capturing devices may be utilized for monitoring babies' breathing while they sleep based on sounds made by the babies during sleep.
The multimedia capturing devices may implement or utilize content recognition solutions for analyzing the different types of multimedia content. Such solutions are designed to process, analyze, and understand multimedia content from the real world in order to produce numerical or symbolic information to reach certain decisions. A decision in multimedia content analysis may be, for example, a detection of an irregular pattern throughout the multimedia content.
Various techniques for pattern recognition are disclosed in the related art. However, due to the fact that patterns are often evenly distributed within the data, recognition of uncommon patterns typically requires extensive computing resources. Specifically, some patterns can be more prominent than others. Such patterns are likely to have a larger number of occurrences, while other patterns may be very rare. In addition, some patterns may be correlated to each other, and together such patterns form pattern-combinations which may also be very popular. This poses a problem to applications for pattern recognition systems.
As pattern recognition is not an easy problem to solve, detection of deviations from such patterns also poses similar challenges as well. Therefore, the ability to identify irregular events by analysis of multimedia content may be limited.